Objective: General Analysis


1. Set Up

README

In general, the data sets are relatively large, and take up a large amount of memory after loading. It is recommended that after loading, that the data sets be subsetted or summarised, and unused data frames to be removed.

The code is shown in the next three tabs to show any changes that may have been made. In general, no columns or rows are removed. Filtering occured in the next step.


General

Loading 1850


Loading 1880


Loading 1910


Combining all time periods, applying occ_modifier

## Parsed with column specification:
## cols(
##   year = col_double(),
##   age = col_double(),
##   sex = col_character(),
##   race = col_character(),
##   city = col_character(),
##   enumdist = col_double(),
##   ward = col_double(),
##   occstr = col_character(),
##   occstr_mod = col_character(),
##   occ = col_double(),
##   occ_label = col_character(),
##   occ_cat_label = col_character(),
##   occ1950 = col_double(),
##   occ1950_label = col_character(),
##   occ1950_cat_label = col_character(),
##   ind1950 = col_double(),
##   ind1950_label = col_character(),
##   ind1950_cat_label = col_character()
## )


shp Files

## Reading layer `Ward_1850_BK' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\bk_shapefiles\Ward_1850_BK.shp' using driver `ESRI Shapefile'
## Simple feature collection with 11 features and 3 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: -8240555 ymin: 4958954 xmax: -8226921 ymax: 4969322
## epsg (SRID):    3857
## proj4string:    +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs
## Reading layer `Ward_1850_MN' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\mn_shapefiles\Ward_1850_MN.shp' using driver `ESRI Shapefile'
## Simple feature collection with 19 features and 3 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: -8239443 ymin: 4968339 xmax: -8227670 ymax: 4994306
## epsg (SRID):    3857
## proj4string:    +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs
## Reading layer `ED_1880_S4_BK' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\bk_shapefiles\ED_1880_S4_BK.shp' using driver `ESRI Shapefile'
## Simple feature collection with 250 features and 152 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: -8240479 ymin: 4958979 xmax: -8226015 ymax: 4973979
## epsg (SRID):    3857
## proj4string:    +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs
## Reading layer `ED_1880_MN' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\mn_shapefiles\ED_1880_MN.shp' using driver `ESRI Shapefile'
## Simple feature collection with 662 features and 41 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: -8239612 ymin: 4968158 xmax: -8227670 ymax: 4994306
## epsg (SRID):    3857
## proj4string:    +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs
## Reading layer `Brooklyn_1910' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\bk_shapefiles\Brooklyn_1910.shp' using driver `ESRI Shapefile'
## Simple feature collection with 1112 features and 1 field
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: 1825539 ymin: 556929.4 xmax: 1841193 ymax: 576192.4
## epsg (SRID):    NA
## proj4string:    +proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs
## Reading layer `Manhattan_1910' from data source `C:\Users\Clinton\Documents\GitHub\hnyc_occupations\Data\shpfiles\mn_shapefiles\Manhattan_1910.shp' using driver `ESRI Shapefile'
## Simple feature collection with 1480 features and 1 field
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: 1823260 ymin: 568821.3 xmax: 1831540 ymax: 591889.7
## epsg (SRID):    NA
## proj4string:    +proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=37.5 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m +no_defs

2. Analysis of Demographics

Age

Sex

Percent of Labor Force


Race

Percent of Labor Force


City

Percent of Labor Force


3. Top 10s Analysis

Occupation

Datatable of General Counts
Overall
  • Across years, Operative and kindred workers (n.e.c.), Managers, officials, and proprietors (n.e.c.), Private household workers (n.e.c.) and Laborers (n.e.c.) appear to be the occupations which consistently are the most common


1850


1880


1910


Graph of General Counts
Percent of Labor Force


Occupation Categories

Datatable of General Counts
Overall
  • Across years, Operative and kindred workers (n.e.c.), Managers, officials, and proprietors (n.e.c.), Private household workers (n.e.c.) and Laborers (n.e.c.) appear to be the occupations which consistently are the most common


1850


1880


1910


Graph of General Counts
Percent of Labor Force


Industry

Datatable of General Counts
Overall


1850


1880


1910


Graph of General Counts
Percent of Labor Force


Industry Categories

Datatable of General Counts
Overall


1850


1880


1910


Graph of General Counts
Percent of Labor Force


4. Maps of Counts

1850

Leaflet Map of Counts
Distributions of Occupation

Occupation


Normalised by size of each ward


Grouped


Normalised and grouped by size of each ward


Distributions of Race

Race


Normalised by size of each ward


Grouped


Normalised and grouped by size of each ward


1880

Leaflet Map of Counts
Distributions of Occupation


Occupation


Normalised by size of each enumeration district


Grouped


Grouped and Normalised by size of each enumeration district


Distributions of Race


Race


Normalised by size of each enumeration district


Grouped


Grouped and Normalised by size of each enumeration district


1910

Leaflet Map of Counts


Distributions of Occupation


Occupation


Normalised by size of each enumeration district


Grouped


Grouped and Normalised by size of each enumeration district


Distributions of Race


Race


Normalised by size of each enumeration district


Grouped


Grouped and Normalised by size of each enumeration district


6. Heatmaps of Combinations

Occupation


Industries